Incubating Göttingen Cultural Analytics Alliance (SUB 2021)
1. a proposal for collaboration between
GWDG ⇋ SUB ⇋ GCDH ⇋ CIDAS ⇋ GBV ⇋ …
Péter Király (pkiraly@gwdg.de), 2021-07-16
incubating……………..
Göttingen Cultural
Analytics Alliance
source
of
image:
https://link.soc.northwestern.edu/research/
https://bit.ly/incubating-gcaa
2. cultural analytics
term coined by Lev Manovich (CUNY), 2007
digital cultural
heritage data
computational
methods
digital
forensics
statistics
quality assessment
data
phenomenology
historical network analysis
stylometry
topic modeling
geospatial
analysis
probability
(meta)data
standards
semantic
technologies
visualisation
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3. scientific/professional domains/activities
digitized cultural
heritage data
computational
methods
computational archival
science
computational
social sciences
carpenties
data science
competitions
Programming Historian
digital
library
digital
humanities
computational
humanities
collections as data &
heritage data reuse charter
academic
courses
bibliographic
data science
data
journals
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4. institutional problems (as I see it)
Connect the dots!
the
secret
expert
connected
experts
disconnected
experts
connected leaders
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organisations at the campus
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5. collaboration levels
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sharing information (interest group)
ad-hoc collaboration
collaboration in
project
regular
collaboration
(working group)
new
organisation
loose
close
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6. collaboration topics
1. service development (local and remote)
2. research
3. education (students, colleagues)
4. open source software development
5. side effect: community building
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7. 1. service development
★ existing metadata services
○ library catalogue
○ MINE
○ GRO.data, GRO.publications
○ bibliometrics
★ new service: QA catalogue – quality dashboard of a catalogue
○ partners: external cultural heritage institutions
○ detailed plan: https://pad.gwdg.de/_9UXRmA3TG2k62MLbHZOfg
○ running example: http://gent.qa-catalogue.eu
★ external services & consultancy
○ open data initiatives: WikiCite, OpenCitations,
○ research data graph: DataCite, Crossref
○ fixing metadata-driven media services (crazy idea: Spotify, Netflix, etc.)
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8. 2. research
★ existing proposals (MOPAD), ongoing projects (Text+?)
★ non-funded research projects → funded projects (MAQUIS)
★ topics for future projects
○ metadata quality assessment
○ cultural heritage data driven historical-sociological research
○ heritage data as research data (as in ‘collections as data’, ‘heritage reuse
charter’ initiatives)
○ bibliometrics, scientometrics
○ AI on heritage data (→ LIBER DS WG, Fantastic Futures, AI4Lib)
○ IIIF
○ TextAPI
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9. 3. education
★ university curriculum
○ for data/computer science:
about the special features of cultural heritage data
○ for (digital) humanities:
introduction to data science - in the context of cultural heritage data
○ for library, archives and museum studies (outside of Göttingen):
introduction to data science - in the context of cultural heritage data
★ further development
○ carpentries
○ Programming History
★ informal
○ participating in existing informal further development frameworks (meetups, R
ladies, Hacky Hour)
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10. 4. open source software development
★ FOLIO
★ Dataverse
★ MINE
★ Metadata Quality Assessment Framework
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11. collaboration with external partners
★ British Library
★ Deutsche Digitale
Bibliothek
★ Europeana
★ BWZ
★ ABES (Fr)
★ Meemoo (Be)
★ Victoria and Albert
Museum
★ Rijksmuseum (Nl)
★ Harvard IQSS
★ BibliotheksVerbund Bayern
partner
Göttingen
Cultural
Analytics
Alliance
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12. established collaborations
★ data analysis
○ general metadata assessment: Meemoo (Flemish Institute for Archives, B),
Victoria and Albert Museum (GB)
○ specific metadata assessment: Europeana, Deutsche Digitale Bibliothek
○ MARC assessment: Gent (B), British Library (GB), BibliotheksVerbund Bayern (D),
Rijksmuseum (NL), U of Szeged (H), Deutsche Nationalbibliothek (D), Koninklijke
Bibliotheek van België (B), Studijní a vědecká knihovna Plzeňského kraje (CR),
Biblioteksentralen (NO)
○ subject indexing (MAQUIS) in planning phase: ABES (Fr), BWZ (D), GBV
★ data-driven research
○ MOPAD: Czech and Polish Academy of Science, U of Helsinki (F), U of Szeged (H)
★ software development
○ Dataverse: Harvard IQSS (US)
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13. next steps
★ establish the network of cultural analysts
★ looking for funding opportunities
○ MAQUIS (Mesurer et Analyser la Qualité de l'Indexation Sujet/Measure and
Analyze the Quality of Subject Indexing):
■ in planning phase
■ partners: GBV, BWZ, ABES (Agence bibliographique de l'emseignement
supérieur)
■ problem: the scale might be small for international proposal
★ looking for student helpers
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